nike_stores

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations at all, the description carries the full burden, and it does a solid job: it discloses the return fields (name, address, phone, coordinates, distance, store page URL) and the well-formed empty result for no-match locations. It stops short of covering areas like pagination limits or error conditions, but for a simple store-finder read it gives meaningful behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, zero filler: the first establishes the action, the second specifies the source and return shape, and the third covers the empty-result edge case. The information is front-loaded and every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description's explicit list of returned store fields fills that need well. Combined with the empty-result behavior and the schema's defaulted parameters (page, radius_miles), an agent has enough to call the tool and interpret the response correctly; the only minor gaps are pagination semantics and error-handling detail.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so lat, lng, page, and radius_miles are all described within the input schema itself. The description reinforces the 'coordinates and radius' concept but adds no new syntax, unit clarification, or edge-case detail beyond what the schema already provides, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

"Find nearby Nike stores" states a concrete verb and resource, and the next sentence pins it to Nike's physical retail store locator. This clearly differentiates it from nike_product, nike_categories, and nike_search, which deal with the online catalog rather than brick-and-mortar locations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the intended use case—geographic proximity lookup by coordinates and radius—but it never explicitly names sibling alternatives or states when not to use it. An agent can infer the right moment from the wording, but the guidance is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.